Digital Oil Field
This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
This paper presents a novel reservoir engineering/reservoir simulation approach—a data-driven interwell-connectivity model augmented as a digital twin—to predict reservoir dynamics and optimize operations in the Changqing oil field of China.
This work uses a novel pseudosteady-state-based simulation to reduce training-data-generation cost while maintaining high-performance predictions of data-driven proxy models for carbon-sequestration projects.
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The smart multilateral well has assisted in addressing premature water breakthrough, has enhanced water-free oil production, and has facilitated uniform depletion, which results in improved hydrocarbon recovery. -
Silixa’s iDAS (intelligent Distributed Acoustic Sensor) offers a solution for permanent and continuous downhole production monitoring and reservoir monitoring by overcoming the cost and technology challenges encountered with traditional point sensors.
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